Digital soil mapping for variable-rate fungicide application in corn and soybeans
A precision agriculture approach using digital soil mapping to predict soil drainage classes and guide variable-rate foliar fungicide application. Field trials show poorly drained soils respond with 14 bu/ac yield gains in corn versus 3 bu/ac on well-drained soils, enabling targeted, more profitable fungicide use.
Overview
This solution leverages Digital Soil Mapping (DSM) to identify soil drainage classes and optimize foliar fungicide application in corn and soybean production. By combining topography, yield data, imagery, and electromagnetic conductivity layers, DSM predicts soil series across fields, enabling variable-rate (VR) fungicide prescriptions that target poorly drained areas where disease pressure and yield potential are highest.
The core value proposition is reduced fungicide input costs combined with improved yields on the parts of the field most likely to benefit. Corn trials showed a mean yield increase of 14 bu/ac on poorly drained soils compared to only 3 bu/ac on well-drained soils when fungicide was applied at VT, indicating strong economic returns from drainage-based variable application.
Technical specifications
How it works:
- Digital Soil Mapping integrates multiple data layers including satellite and aerial imagery, historical yield maps, topographic data, and electromagnetic conductivity sensors to predict soil series across a field
- Predicted soil series are classified by drainage class (poorly drained versus well drained)
- Variable-rate prescription scripts are generated and sent directly to the sprayer, turning fungicide on over poorly drained soils and off over well-drained soils
- Yield response is measured using calibrated combine yield monitors, cleaned, and spatially joined to soil data for analysis in GIS software
Key features and applications:
- Tested with Miravis Neo and StrategoPro fungicides on corn across approximately 20 strip trials over four years in collaboration with Woodrill Farms Ltd
- Applicable to corn and soybean production systems where foliar disease management is a concern
- Integrates with existing precision agriculture infrastructure including VR-capable sprayers and yield monitoring equipment
- Disease severity ratings for white mould pressure planned as part of soybean validation
Technology readiness level
The approach has been validated through multiple years of on-farm strip trials in corn, demonstrating consistent yield responses by soil drainage class. The research team is seeking to extend validation to soybeans using StrategoPro, with planned field trials incorporating VR scripts, disease severity ratings, and spatial yield analysis. The technology is at a stage where it can be deployed in collaborative on-farm trials and refined through additional field validation with industry partners.
About University of Guelph
The University of Guelph is a comprehensive, mid-sized public research university in Guelph, Ontario. Industry partners engage through an on-campus research park and the Ontario Veterinary College’s teaching hospitals, which enable product evaluation and clinical translation. The university’s Arboretum and the nearby Agriculture and Agri-Food Canada Guelph Research and Development Centre offer living laboratories and federal linkages that support collaborative R&D. Research is backed by competitive federal funding and strong provincial support via the Ontario Agri‑Food Innovation Alliance. The Research Innovation Office serves as the university’s technology transfer and industry liaison hub, supporting IP, licensing, and co‑funded partnerships.
delivered to your inbox.